Predicting pollination phenology in lodgepole pine
Susannah Tysor
May 8, 2019
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As the climate changes, spring phenological events like budburst and flowering will advance, especially for plants active in rapid seasonal transitions and short growing seasons [@Pau2011], like many high elevation and latitude conifers. This effect is already obvious in many species [@Parmesan2006; @Franks2014]. Changes in pollination phenology can affect fecundity, gene flow, and even range size in a species and have effects on dependent species [@Inouye2008; @Chuine2001a].
Conifers are a big part of the enormous northern northern hemisphere forests and they have wide ranges with lots of local adaptation. Common garden experiments and genetic work reveal extensive local adaptation in many forest tree species, especially boreal and temperate conifers (reviewed in @Alberto2013a). A locally adapted population only grows optimally in a subset of the range and may tolerate a more limited climatic range than the species as a whole. In northern hemisphere conifers, local adaptation often reflects strong trade-offs between avoidance of cold damage and competitive height growth (summarized in @Aitken2008a).
Coniferous forest trees are wind pollinatated wtih pollination possible over large distances Pollen is shed from male strobili and must arrive at receptive female strobili for successful pollination. Shifts in the timing of pollen shed and cone receptivity (pollination phenology) in conifers could lead to gene flow changes that hinder or promote adaptation under climate change, decrease fitness, and even affect reforestation via seed production declines. [Also affects gene flow now and is important for understanding current spatial genetic structure and local adaptation]
Lodgepole pine is a good representative of these issues - an economically and ecologically important tree species facing multiple threats from climate change [@Schneider2010; @Sambaraju2012; @Hamann2006]. Lodgepole pine has a very large geographical distribution (across 33\(^\circ\) latitude and 31\(^\circ\) longitude) encompassing a wide range of climates and soils (Figure ) with widespread and significant local adaptation in many traits. For example, populations from both northern interior British Columbia and northern Idaho can survive in areas with mean annual temperatures between -4 and 6 \(^\circ\mathrm{C}\), but the northern British Columbia population survives best where mean annual temperatures are ~ 1 \(^\circ\mathrm{C}\) and the Idaho population best at ~ 4 \(^\circ\mathrm{C}\) [@Rehfeldt1999a]. Local adaptation in lodgepole pine can be observed even at relatively small spatial scales when topographic variability is high: in a reciprocal transplant experiment, growth declines were observed when moving high elevation populations just 100m in elevation [@Rehfeldt1983]. [Summarize/cite adaptree work]
Pollen is an important vector for identifying gene flow in lodgepole pine because outcrossing is common, pollen dispersal is extensive, and seed dispersal is relatively limited [@Ennos1994]. There is evidence for spatially varying levels of gene flow in the species as populations from areas with higher regional climate heterogeneity have higher genetic variance [@Yeaman2006]. Pollination phenology could control this.
Pollination phenology determines which populations can exchange genes, but predicting the timing of pollen shed and cone receptivity has not been done in lodgepole pine. Pollination phenology examples are uncommon. [Talk about Sarvas investigations for mechanistic background, why using temperature, etc.] Simple heat accumulation thresholds (Pinus taeda) [@Boyer1978] or elevation (Pinus flexilis) [@Schuster1989] were used previously to explain or predict pollen shed in limited spacial and temporal contexts. @Owens2006 reports that lodgepole pine pollen shed and cone receptivity occur when degree days reach about 500 at a threshold of 5 \(^\circ\mathrm{C}\), but this is the only report of pollination phenology modeling for lodgepole pine and limited details are provided. Models of lodgepole pine vegetative phenology, on the other hand, are better represented in the literature (e.g. @Chuine2001), and pollen shed and cone receptivity are not expected to have additional or more complex triggers or model forms than budburst [@Chuine2013a].
Predicting pollination phenology will also have practical benefits. Seed orchard managers in British Columbia are particularly concerned about protandry, when all pollen in an area is shed before cones become receptive (personal communication, Chris Walsh, Former Seed Orchard Manager, Kalamalka Seed Orchards, February 13, 2013). Protandry occurs in particularly hot and dry years [@Owens2005]. If this pattern holds, protandry could become more common in natural populations, leaving some populations pollen limited and likely hampering local adaption. [Outcrossing! Inbreeding!]
This paper relies on 15 year pollination phenology data set collected in British Columbia lodgepole pine seed orchards. Seed orchards produce seed for reforestation. While not set up as common gardens, several provenances are typically represented at each site allowing testing for provenance effects and genetic x environmental interaction. and genotypes usually appear multiple times within a site and sometimes at multiple sites.
I will use pollination phenology and temperature data to fit a mechanistic model predicting pollen shed and cone receptivity across the entire range of Pinus contorta var. latifolia and consider how the date and length of pollination phenology periods vary normally and under several climate change scenarios. Specifically, I will answer 1) What is the relationship between temperature and pollen shed and temperature and cone receptivity timing and length? 2) Does provenance affect that relationship? 3) How many days will pollination phenology shift under the next 30, 60, and 90 years of climate change 4) Will protandry become more common?
Methods
My aim was to model pollination phenology in lodgepole pine and calculate synchrony across the distribution. To determine the timing of pollen shed and cone receptivity, I modeled the forcing requirements for pollination phenology in lodgepole pine and investigated differences in forcing requirements between males and females and among provenances.
Study species
Lodgepole pine is a wind-pollinated conifer with an extensive range and well documented local adaptation. While lodgepole pine has four subspecies, this work concerns only Pinus contorta subsp. latifolia. Pollen and seed cone buds differentiate in late summer and early fall, then go dormant. As temperatures warm the following year, buds resume development and strobili “flower”; receptive female strobili exude pollination drops between bracts that capture pollen shed from mature male strobili.
Rangemap of lodgepole pine. After @Little1971 .
Data
Phenology Data
This project takes advantage of an existing lodgepole pine pollination phenology dataset collected over a decade and a half by government and industry workers in seed orchards. Seed orchards in British Columbia produce large amounts of tree seed for reforestation from parent trees sourced from provenances around the province. In the 90s, it became apparent that seed yields at seed orchards in the southern interior were much lower than in more northern seed orchards. To plan for future seed production and orchard establishment and management, seed orchard managers monitored pollination phenology and seed production to understand why seed yields at north Okanagan orchards were lower than at the Prince George Tree Improvement Station orchards. Pollination phenology data was collected at the Prince George Tree Improvement Station in British Columbia beginning in 1997 and collection at many other BC tree orchard sites began in 2006 under the Forest Genetics Council’s Operational Tree Improvement Program 0722 [@Webber2007].
Sites
Trees selected from across the British Columbia portion of the lodgepole pine range are grown in seed orchards as part of tree breeding and seed production programs. Between 1997 and 2011, flowering phenology of lodgepole pine was recorded at 7 seed orchard sites in the interior of British Columbia. I contacted Seed Orchard Managers and other forestry professionals across British Columbia in 2012 and received pollination phenology data from C. Walsh, previously at Kalamalka Seed Orchards (now retired), R. Wagner at the Prince George Tree Improvement Station, and J.E. Webber previously at the Glyn Road Research Station (now retired). 4 of the sites are clustered near to one another, but sites span about 5 \(^\circ\) of latitude and are at elevations from 466 to 638 m.
Map of seed orchard locations. Boxed area in map on left is shown in greater detail on the right.
Provenances
Trees grown at the seed orchard sites were sourced from 6 biogeoclimate regions known as Seed Planning Units (SPUs). Trees with the same SPU provenance are grown together in an orchard at a given site. Genotypes (labelled with a Clone number in the data) in the orchards are represented by multiple ramets.
I obtained pollination phenology records from 17 of the 26 lodgepole pine seed orchards in British Columbia. Orchards include the offspring of trees from 6 of the 7 BC seed planning zones (SPZs) (Figure ) grown at at 7 sites across BC. SPZs are biogeoclimatic and political units used for seed planting purposes by British Columbia. SPZs are divided into elevation bands called Seed Planning Units (SPUs), which form this project’s provenances.
Thirteen out of 17 orchards in my data set are first generation orchards and should faithfully represent their provenances. These first generation orchards represent 6 provenances at 5 sites. Second generation orchards have been selectively crossed and this may skew the mean or variance of phenology for a provenance if pollination phenology varies by provenance.
Most provenances are represented at 2 to 3 sites and have at least three years of data at a given site spanning 1997-2012 (Figure ). The Prince George Tree Improvement Station (PGTIS) provides a continuous 15-year record of its three orchards’ phenology.
Contingency table of years of data for Seed Planning Units (rows) and Seed Orchard Sites (columns). Seed Planning Zones, used as provenances in this project, are usually represented at multiple years and multiple sites. There is particularly good representation at PGTIS.
Map of Seed Planning Units (SPUs). Seed planning units are biogeoclimatic and political units used for seed planting purposes by British Columbia. Seed planning units form this project’s provenances. High, Low, and Mid refer to elevational bands. Data is also available for East Kootenay Low, but will likely not be included in any analysis as it includes only one year at one site.
[table with Site Columns and SPU rows with years of data as values][table of number of trees/clones in a given year for a given site/spu combo]
Phenology scoring protocol
Protocol C in [@Woods1996] was used as the basis for collecting pollen shed and cone receptivity data, though operational constraints led to some modifications. Workers monitored seed orchards for the beginning of pollen shed and cone receptivity. ~15 clones, usually represented by 2 trees each, were selected for specific observations. When the active period seemed to be starting, workers went into the orchard every few days to make observations on the selected trees.
Stages of pollen and seed cone development are described by [Owens & Molder 1984 and updated in Owens2006] and were used as a general guide for determining the phenological state of pollen and seed cones. Pollen cones are flowering when tapping causes pollen to be released and seed cones are flowering when there are gaps between the bract-scale complexes. Pollination drops are also produced during flowering, though they recede midday if pollen is not present [@Owens2006].
“Flowering” states were recorded for both pollen shed and cone receptivity at the level of each tree. Protocol C recommends marking the dates when 20% of the cones on a tree have begun flowering and when 80% of the cones on a tree have finished flowering. Operationally, there was some subjectivity and tree-level states for each cone type should be interpreted as “starting flowering” and “finished flowering.” There is some subjectivity here.
[DESCRIBE SURVEY PERIODS, MAYBE MAKE A TABLE OR GRAPH OF OBSERVATION DATES?]
Observations were not made every day and survey periods varied in length. At Prince George, not all trees have complete phenological records, e.g if a tree is not flowering on the first day of observation, the start date is unknown.
Harmonization and cleaning
Describe data transcription and cleaning.
There were some differences in how data was recorded at the Prince George Tree Improvement Station versus the other sites. At Prince George, trees were marked as flowering or not flowering on each day of observation. At other sites, only the first day observed flowering and the first day observed finished flowering were recorded. I inferred that trees were not yet flowering on observation days prior to their first recorded flowering date. I cleaned and harmonized the data for analysis in a single model using R scripts provided so that, for pollen cones and seed cones, stage 1 = not yet flowering, stage 2 = flowering, and stage 3 finished flowering.
There are three phenological stages of interest each for a tree’s male and female cones
- The cones have not yet flowered
- The cones are flowering
- The cones have finished flowering
Phenophases in the field were recorded using different symbol sets and resolutions. I assigned each symbol to one of the phenophases above. Trees that did not produce cones are assigned phenological stage 0.
| Phenophase | Symbols | Male.Cones | Female.Cones |
|---|---|---|---|
| 0 | 0 | none produced | none produced |
| 1 | 1, 2.5, - | not yet shedding | not yet receptive |
| 2 | 3, 3.5, 4, 4.5, 5, pollenshed20, receptive20 | shedding | receptive |
| 3 | -, receptive80, pollenshed80 | finished shedding | no longer receptive |
Weather data
Daily weather data at seed orchard sites was extracted from PNWNAmet, a daily gridded meteorological dataset at 1/16 \(^\circ\) over northwest North America [@pacificclimateimpactsconsortiumPNWNAmet194520122014]. The closest point in the PNWNAmet was used for each station. Mean daily temperature was calculated from the minimum and maximum daily temperatures.
